[phenixbb] Strong anomalous signal but AutoSol fails
mohamed noor
mohamed.noor34 at gmail.com
Fri Aug 7 09:55:09 PDT 2015
Hi Tom
Just to check that I am on the right track, I have attached below the
output from phenix.anomalous_signal using a single XDS_ASCII.HKL file from
a single crystal. It is one of a few datasets, but based on Xtriage seems
to be the best one.
The space group is P 3(1/2) 2 1. All datasets were collected at the peak
wavelength (fluorescence scan). My initial feeling that there is a strong
signal comes from CORRECT.LP. Aimless and Xtriage. IIRC, the resolution
difference between the optimistic and pessimistic measurability is about
0.3-0.4 A.
Estimation of anomalous signal in a dataset
Estimating B-value for anomalous substructure as 91.2 based on
overall B-value of 75.4 (Note: you can set this with
b_value_anomalous=xx)
Getting scaled data and half-datasets with scale_and_merge
Log file will be: scale.log
Files for half_dataset CC:
['TEMP4/XDS_ASCII_SG150_1800frames_reprocFriedel_0_1.sca']
Files for half_dataset CC:
['TEMP4/XDS_ASCII_SG150_1800frames_reprocFriedel_0_1.sca']
Files for half_dataset CC:
['TEMP4/XDS_ASCII_SG150_1800frames_reprocFriedel_0_1.sca']
Scaled data are in: scaled_data.mtz
Half-dataset A is in: half_dataset_a.mtz
Half-dataset B is in: half_dataset_b.mtz
Using scaled data in analysis
Setting up estimator for CC*
-------------------Summary of signal in this dataset
------------------------
Shell
CCano Nrefl Nrefl
Resolution Esqr I/sigI half anom half
47.8- 7.0 0.50 19.55 0.32 2389 2360
7.0- 6.5 0.69 10.63 0.11 621 608
6.5- 6.0 0.87 8.47 0.08 850 818
6.0- 5.5 0.88 7.52 0.08 1189 1141
5.5- 5.0 0.72 5.88 0.09 1709 1588
5.0- 4.5 0.76 4.59 0.07 2521 2247
4.5- 4.0 0.98 3.25 0.05 3881 3268
4.0- 3.5 0.79 3.23 0.24 4001 2577
3.5- 3.3 1.72 1.99 -0.02 3420 2118
Cumulative
----------------------Data quality----------------- Best guess of
expected
results of finding
sites
------ and
phasing--------
CCano Nrefl P(Substr)
Resolution Skew Esqr half anom CC* Signal +/- (%) FOM* +/-
47.8- 7.0 0.02 0.47 0.32 2389 0.51 10.1 1.3 68 0.2 0.0
47.8- 6.5 0.02 0.50 0.28 3010 0.48 10.7 1.7 72 0.2 0.1
47.8- 6.0 0.02 0.57 0.24 3860 0.43 10.8 2.8 72 0.2 0.1
47.8- 5.5 0.05 0.64 0.20 5049 0.44 12.6 2.4 78 0.2 0.1
47.8- 5.0 0.01 0.66 0.17 6758 0.39 12.8 3.3 78 0.2 0.1
47.8- 4.5 0.01 0.69 0.14 9279 0.36 13.4 3.4 82 0.2 0.1
47.8- 4.0 0.00 0.77 0.12 13160 0.33 14.3 3.6 88 0.2 0.1
47.8- 3.5 0.00 0.77 0.15 17161 0.39 18.4 3.8 98 0.3 0.1
47.8- 3.3 0.00 0.88 0.14 20581 0.31 15.7 2.1 95 0.2 0.0
On Fri, Aug 7, 2015 at 2:30 PM, Terwilliger, Thomas Charles <
terwilliger at lanl.gov> wrote:
> Hi Mohamed,
>
> You might try running phenix.anomalous_signal on your data (may require
> finding your unmerged data and running phenix.scale_and_merge first). This
> will give you an idea if you should be able to solve your SAD dataset.
>
> See:
> http://www.phenix-online.org/version_docs/1.10pre-2124/reference/anomalous_signal.html
>
> All the best,
> Tom T
>
>
>
>
>
> From: phenixbb-bounces at phenix-online.org [
> phenixbb-bounces at phenix-online.org] on behalf of mohamed noor [
> mohamed.noor34 at gmail.com]
>
> Sent: Thursday, August 06, 2015 3:16 PM
>
> To: PHENIX user mailing list
>
> Subject: [phenixbb] Strong anomalous signal but AutoSol fails
>
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> Dear developers
>
>
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> I have a low resolution anomalous dataset which Aimless suggests has an
> effective resolution to 3.3 A and anomalous signal to 3.5 A. However, SAD
> phasing with AutoSol is not successful with the final R factor around 50 %.
>
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> I also have another dataset collected at a remote wavelength without
> anomalous signal to 3 A but they are not isomorphous (> 2 A difference in c
> axis).
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> The anomalous signal comes from the ligand heme c, which is bound
> covalently to the protein, so its occupancy should be 1. The protein is
> quite small with about 120 residues. Xtriage suggests an NCS of 6 to 20
> with most likely number to be 13.
>
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> Is there any reason why a reasonable solution cannot be found? There is no
> twinning.
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> I am using the latest nightly 1.10 pre2124.
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> Thanks.
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>
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